For end to end devops automation I want to have an environment on demand. For this I need to Spun up and environment on kubernetes which is eventually hosted on GCP.
My Use case
1. Developer Checks in the code in feature branch
2. Environment in Spun up on Google Cloud with Kubernetes
3. Application gets deployed on Kubernetes
4. Gets tested and then the environment gets destroyed.
I am able to do everything with Spinnaker except #2. i.e create Kube Cluster on GCP using Spinnaker.
Any help please
Thanks,
Amol
I'm not sure Spinnaker was meant for doing what the second point in your list. Spinnaker assumes a collection of resources (VM's or a Kubernetes cluster) and then works with that. So instead of spinning up a new GKE cluster Spinnaker makes use of existing clusters. I think it'd be better (for you costs as well ;) if you seperate the environments using Kubernetes namespaces.
Related
On the Ignite website, I see that in Amazon EKS, Microsoft Azure Kubernetes Service Deployment, and Google Kubernetes Engine Deployment, deploy on each of the three platforms ignite.If I am on my own deployed K8S, can I deploy?Is it the same as deploying the Ignite on three platforms?
Sure, just skip the initial EKS/Azure initialization steps since you don't need them and move directly to the K8s configuration.
Alternatively, you might try Apache Ignite and GridGain k8s operator that simplifies the deployment.
I have a running Kubernetes cluster on Google Cloud Platform.
I want to deploy a postgres image to my cluster.
When selecting the image and my cluster, I get the error:
insufficient OAuth scope
I have been reading about it for a few hours now and couldn't get it to work.
I managed to set the scope of the vm to allow APIs:
Cloud API access scopes
Allow full access to all Cloud APIs
But from the GKE cluster details, I see that everything is disabled except the stackdriver.
Why is it so difficult to deploy an image or to change the scope?
How can I modify the cluster permissions without deleting and recreating it?
Easiest way is to delete and recreate the cluster because there is no direct way to modify the scopes of a cluster. However, there is a workaround. Create a new node pool with the correct scopes and make sure to delete any of the old node pools. The cluster scopes will change to reflect the new node pool.
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We are using prometheus in our production envirment recently. Before we only have 30-40 nodes for each service and those servers not change very often, so we just write it in the prometheus.yml, but right now it become too long to hold in one file and change much frequently then before, so my question is should i use file_sd_config to put those server list out of yml file and change those config files sepearately, or using consul for service discovery(same much easy to handle changes).
I have install 3 nodes consul cluster in data center and as i can see if i change to use consul to slove this problem , i also need to install consul client in each server(node) and define its services info. Is that correct? or does anyone have good advise.
Thanks
I totally advocate the use of a service discovery system. It may be a bit hard to deploy at first but surely it will worth it in the future.
That said, Prometheus comes with a lot of service discovery integrations. It's possible that you don't need a Consul cluster. If your servers are in a cloud provider like AWS, GCP, Azure, Openstack, etc, prometheus are able to autodiscover the instances.
If you keep running with Consul, the answer is yes, the agent must be running in every node. You can also register services and nodes via API but it's easier to deploy the agent.
I just started trying out Spinnaker. I have gone through the tutorial, https://www.spinnaker.io/guides/tutorials/codelabs/gcp-kubernetes-source-to-prod/, and got it working without issues.
Now I want to go a bit more advanced and do a rolling release or a canary deployment (https://www.spinnaker.io/concepts/#deployment-strategies), where it is possible, for instance, to only expose a new release to 5% of the customers.
I cannot find any guide on spinnaker.io (or google) on how to set that up. Can anyone guide me in the right direction?
I have currently been experimenting and doing PoC's on Spinnaker and Canary Deployments myself of late, and here is what I have found thus far.
To implement a rolling release, just create a Deploy stage in Spinnaker, and set the Deployment Strategy to RollingUpdate in your Server Group config. You will need to make sure that the Deployment checkbox is checked before you can change the Deployment Strategy.
For the Canary Deployment, it is a little more involved. I don't think that the Canary Stage currently supports Kubernetes Deployments(yet), but apparently you can manually deploy a canary(e.g. 1 replica) into the same Kubernetes LoadBalancer where your app is running. This is done using a separate Spinnaker Server Group.
Then you can add a Manual Judgement to your Spinnaker pipeline that will pause until you test/validate the canary. Once the canary has been validated, you "Continue" the Manual Judgement, and the new Server Group gets deployed, and the old Server Group gets disabled, and the canary destroyed.
If you don't want to use a Manual Judgement, and want this fully automated, you can add an ACA Stage(Automated Canary Analysis). This involves setting up a judge, that Spinnaker can connect to, that will gather various metrics and provide an ACA score. You can then use that score to decide whether to proceed with a deployment, or stop the deployment.
We are looking for a solid, declarative (yaml), based proceedure to automate the setup of our Kubernetes cluster and application deployments on Google Container Engine.
As our last resort in a serious failure we want to be able to:
Create a new GCE cluster
Execute all our deployments to their latest versions
Execute all the steps in the correct order
What are the solutions people are currently using. Doing this manually takes us about an hour and is error prone. Really it could take 15-20 mins if automated.
You should take a look at Google Cloud Deployment Manager. It "automates the creation and management of your Google Cloud Platform resources for you" meaning that it can create a Google Container Engine cluster as well as create your deployments.
Looking through the GKE deployment manager example should help get you started.